Sky littoral sites
SB1 <- read_csv(here("data/SB1_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
SB2 <- read_csv(here("data/SB2_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
SB3 <- read_csv(here("data/SB3_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
SB4 <- read_csv(here("data/SB4_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
SB5 <- read_csv(here("data/SB5_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
Loch littoral sites
LB1 <- read_csv(here("data/LochInlet_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
LB3 <- read_csv(here("data/LB3_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
LB4 <- read_csv(here("data/LB4_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
LB5 <- read_csv(here("data/LB5_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
LB6 <- read_csv(here("data/LB6_2016.csv")) %>%
mutate(dateTime = mdy_hm(dateTime))
Master littoral
sky_littoral <- bind_rows(SB1, SB2, SB3, SB4, SB5) %>%
mutate(habitat = "littoral")
loch_littoral <- bind_rows(LB3, LB4, LB5, LB6, LB1) %>%
mutate(habitat = "littoral")
littoral_master <- bind_rows(sky_littoral,
loch_littoral) %>%
mutate(dateTime = round_date(dateTime, "hour")) #For making joining to pelagic data easier
sky_buoy_long <-
read.table(here("data/sky_2016_tempProfile.txt"),
sep = ",",
header = TRUE) %>%
mutate(
dateTime = ymd_hms(as.factor(dateTime)),
dateTime = force_tz(dateTime, tz = "America/Denver"),
dateTime = with_tz(dateTime, "GMT")
) %>%
filter(dateTime >= "2016-06-13" &
dateTime <= "2016-10-30") %>% #ice off and on dates
rename(wtr_6.5 = wtr_7.0) %>%
pivot_longer(-dateTime, names_to = "depth") %>%
mutate(habitat = "pelagic") %>%
separate(col = depth,
into = c("parameter", "depth"),
sep = "_") %>%
mutate(parameter = "temperature",
lakeID = "SkyPond")
loch_buoy_long <- read.table(here("data/loch_2016_tempProfile.txt"), sep=",", header=TRUE) %>%
mutate(dateTime = ymd_hms(as.factor(dateTime)),
dateTime = force_tz(dateTime, tz="America/Denver"),
dateTime = with_tz(dateTime, "GMT")) %>%
filter(dateTime > "2016-05-31" & dateTime <= "2016-10-30") %>% #ice off and on dates
pivot_longer(-dateTime, names_to="depth") %>%
mutate(habitat="pelagic") %>%
separate(col = depth, into = c("parameter", "depth"), sep = "_") %>%
mutate(parameter="temperature",
lakeID="TheLoch")
sky_DO_0.5 <-
read.table(here("data/sky_2016_DO_0.5m.txt"),
sep = ",",
header = TRUE) %>%
mutate(
dateTime = ymd_hms(dateTime),
depth = 0.5,
lakeID = "SkyPond",
habitat = "pelagic"
) %>%
filter(dateTime < "2016-11-02")
sky_DO_6.5 <-
read.table(here("data/sky_2016_DO_6.5m.txt"),
sep = ",",
header = TRUE) %>%
mutate(
dateTime = ymd_hms(dateTime),
depth = 6.5,
lakeID = "SkyPond",
habitat = "pelagic"
) %>%
filter(dateTime < "2016-11-02")
loch_DO_0.5 <-
read.table(here("data/loch_2016_DO_0.5m.txt"),
sep = ",",
header = TRUE) %>%
mutate(
dateTime = ymd_hms(dateTime),
depth = 0.5,
lakeID = "TheLoch",
habitat = "pelagic"
)
loch_DO_4.5 <-
read.table(here("data/loch_2016_DO_4.5m.txt"),
sep = ",",
header = TRUE) %>%
mutate(
dateTime = ymd_hms(dateTime),
depth = 4.5,
lakeID = "TheLoch",
habitat = "pelagic"
)
Combine all DO data
DO_master <- bind_rows(sky_DO_0.5,
sky_DO_6.5,
loch_DO_0.5,
loch_DO_4.5) %>%
rename(value=DO) %>%
mutate(parameter="DO",
depth=as.character(as.numeric(depth)))
Master buoy df
buoy_master <-
bind_rows(DO_master, loch_buoy_long, sky_buoy_long) %>%
mutate(
depth_category = case_when(depth == 0.5 ~ "surface",
TRUE ~ "bottom"),
depth_category = factor(depth_category,
levels = c("surface", "bottom")),
season = case_when(dateTime > "2016-09-01" ~ "fall",
TRUE ~ "summer"),
season = factor(season,
levels = c("summer", "fall"))
)
All DO, line graph
Plotting just summer below, where we have overlap with littoral zone measurements
How much does DO fluctuate daily at each depth?
All temps,line graph
Just summer when all sensors were present
How much does temperature fluctuate daily at each depth?
Littoral zones temperature in both lakes, 2016
How large are the diurnal swings?
Histograms of diel temperature swings
How do the littoral zone temperatures compared to 0.5m temperatures? Separate panel for each site
How do the littoral zone temperatures compared to 0.5m temperatures? Include 0.5m depth in the background of each panel